Abstract

The traditional approach of a star tracker for reducing the dynamic error concentrates on a single frame of star images. Through correlating adjacent star images together with their angular relations sensed by a gyroscope unit (GU), the attitude-correlated frames (ACF) approach expands the view from one single frame to frame sequences. However, the star centroid is shifted from the star true position at the center time of the exposure period under complex dynamic conditions, which is called the complex motion induced error (CMIE) in this paper. The CMIE has a large effect on the performance of the ACF approach. This paper presents a method to compensate the CMIE through reconstructing the star trajectory with the angular velocity of the star tracker sensed by a GU, which achieves effective compensation of the CMIE crossing the boresight direction. Since the observation sensitivity to the CMIE along the boresight direction is low, the attitudes from two different fields of view (FOVs) are combined to improve its compensation accuracy. Then the ACF approach is applied to the obtained results where the CMIE has already been compensated completely. Simulations under shipboard dynamic conditions and experiments under oscillating conditions indicate that the proposed method is effective in improving the performance of the ACF approach and reducing the dynamic error of a star tracker under complex dynamic conditions.

© 2017 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

Full Article  |  PDF Article
OSA Recommended Articles
Attitude-correlated frames approach for a star sensor to improve attitude accuracy under highly dynamic conditions

Liheng Ma, Dejun Zhan, Guangwen Jiang, Sihua Fu, Hui Jia, Xingshu Wang, Zongsheng Huang, Jiaxing Zheng, Feng Hu, Wei Wu, and Shiqiao Qin
Appl. Opt. 54(25) 7559-7566 (2015)

Global field-of-view imaging model and parameter optimization for high dynamic star tracker

Zhen Wang, Jie Jiang, and Guangjun Zhang
Opt. Express 26(25) 33314-33332 (2018)

Three-axis attitude accuracy of better than 5 arcseconds obtained for the star sensor in a long-term on-ship dynamic experiment

Liheng Ma, Dongshan Zhu, Chunsheng Sun, Dongkai Dai, Xingshu Wang, and ShiQiao Qin
Appl. Opt. 57(32) 9589-9595 (2018)

References

  • View by:
  • |
  • |
  • |

  1. C. Liu, G. Liu, X. Wang, and A. Li, Principles and Systematic Applications of Missile-Borne Star Sensor (National Defense Industry, 2010).
  2. J. L. Jorgensen, T. Denver, M. Betto, and P. V. d. Braembussche, “The PROBA satellite star tracker performance,” Acta Astronautica 56, 153–159 (2005).
    [Crossref]
  3. R. W. H. v. Bezooijen, “SIRTF autonomous star tracker,” in Astronomical Telescopes and Instrumentation (SPIE, 2003), 14.
  4. W. Zhang, W. Quan, and L. Guo, “Blurred Star Image Processing for Star Sensors under Dynamic Conditions,” Sensors 12, 6712 (2012).
    [Crossref] [PubMed]
  5. K. Wang, C. Zhang, Y. Li, and X. Kan, “A New Restoration Algorithm for the Smeared Image of a SINS-aided Star Sensor,” Journal of Navigation 67, 881–898 (2014).
    [Crossref]
  6. W. Quan and W. Zhang, “Restoration of Motion-blurred Star Image Based on Wiener Filter,” in 2011 International Conference on Intelligent Computation Technology and Automation (IEEE, 2011), pp. 691–694.
  7. T. Sun, F. Xing, Z. You, X. Wang, and B. Li, “Smearing model and restoration of star image under conditions of variable angular velocity and long exposure time,” Opt. Express 22, 6009–6024 (2014).
    [Crossref] [PubMed]
  8. F. Xing, N. Chen, Z. You, and T. Sun, “A Novel Approach Based on MEMS-Gyro’s Data Deep Coupling for Determining the Centroid of Star Spot,” Math. Probl. Eng. 2012, 403584(2012).
  9. S. Qin, D. Zhan, J. Zheng, W. Wu, H. Jia, S. Fu, and L. Ma, “Dynamic attitude measurement method of star sensor based on gyro’s precise angular correlation,” U.S. Patent 9,316,716 (2016).
  10. L. Ma, D. Zhan, G. Jiang, S. Fu, H. Jia, X. Wang, Z. Huang, J. Zheng, F. Hu, W. Wu, and S. Qin, “Attitude-correlated frames approach for a star sensor to improve attitude accuracy under highly dynamic conditions,” Appl. Opt. 54, 7559–7566 (2015).
    [Crossref] [PubMed]
  11. J. Jiang, J. Huang, and G. Zhang, “An Accelerated Motion Blurred Star Restoration Based on Single Image,” IEEE Sensors Journal 17, 1306–1315 (2017).
    [Crossref]
  12. R. A. Fowell, S. I. Saeed, R. Li, and Y.-W. A. Wu, “Mitigation of angular acceleration effects on optical sensor data,” U.S. Patent 6, 863, 244 (2005).
  13. R. A. Fowell, R. Li, and Y.-W. A. Wu, “Method for compensating star motion induced error in a stellar inertial attitude determination system,” U.S. Patent 7, 487, 016 (2009).
  14. T. Sun, F. Xing, X. Wang, Z. You, and D. Chu, “An accuracy measurement method for star trackers based on direct astronomic observation,” Sci. Rep. 6, 22593 (2016).
    [Crossref] [PubMed]
  15. G. Wahba, “A Least Squares Estimate of Satellite Attitude,” SIAM Rev. 7, 409 (1965).
    [Crossref]
  16. C. C. Liebe, “Accuracy performance of star trackers - a tutorial,” IEEE Trans. Aerosp. Electron. Syst. 38(2), 587–599 (2002).
    [Crossref]
  17. D. Titterton and J. L. Weston, Strapdown inertial navigation technology (IET, 2004).
    [Crossref]
  18. L. Ma, F. Bernelli-Zazzera, S. Qin, and X. Wang, “Performance analysis of the attitude-correlated frames approach for star sensors,” in 2016 IEEE Metrology for Aerospace (MetroAeroSpace) (IEEE, 2016), pp. 81–86.
    [Crossref]
  19. L. Ma, C. Hu, X. Wang, and D. Dai, “Advances and accuracy performance of the star trackers,” in ISPDI 2013 - Fifth International Symposium on Photoelectronic Detection and Imaging (SPIE, 2013), 9.
  20. J. Hua, T. Zhang, and H. Zhu, “Star image fusion and star recognition of multi-FOV star sensor,” in Proceedings of 2014 IEEE Chinese Guidance, Navigation and Control Conference (IEEE, 2014), pp. 2111–2125.
  21. J. Yan, J. Jiang, and G. Zhang, “Dynamic imaging model and parameter optimization for a star tracker,” Opt. Express 24, 5961–5983 (2016).
    [Crossref] [PubMed]

2017 (1)

J. Jiang, J. Huang, and G. Zhang, “An Accelerated Motion Blurred Star Restoration Based on Single Image,” IEEE Sensors Journal 17, 1306–1315 (2017).
[Crossref]

2016 (2)

T. Sun, F. Xing, X. Wang, Z. You, and D. Chu, “An accuracy measurement method for star trackers based on direct astronomic observation,” Sci. Rep. 6, 22593 (2016).
[Crossref] [PubMed]

J. Yan, J. Jiang, and G. Zhang, “Dynamic imaging model and parameter optimization for a star tracker,” Opt. Express 24, 5961–5983 (2016).
[Crossref] [PubMed]

2015 (1)

2014 (2)

K. Wang, C. Zhang, Y. Li, and X. Kan, “A New Restoration Algorithm for the Smeared Image of a SINS-aided Star Sensor,” Journal of Navigation 67, 881–898 (2014).
[Crossref]

T. Sun, F. Xing, Z. You, X. Wang, and B. Li, “Smearing model and restoration of star image under conditions of variable angular velocity and long exposure time,” Opt. Express 22, 6009–6024 (2014).
[Crossref] [PubMed]

2012 (2)

F. Xing, N. Chen, Z. You, and T. Sun, “A Novel Approach Based on MEMS-Gyro’s Data Deep Coupling for Determining the Centroid of Star Spot,” Math. Probl. Eng. 2012, 403584(2012).

W. Zhang, W. Quan, and L. Guo, “Blurred Star Image Processing for Star Sensors under Dynamic Conditions,” Sensors 12, 6712 (2012).
[Crossref] [PubMed]

2005 (1)

J. L. Jorgensen, T. Denver, M. Betto, and P. V. d. Braembussche, “The PROBA satellite star tracker performance,” Acta Astronautica 56, 153–159 (2005).
[Crossref]

2002 (1)

C. C. Liebe, “Accuracy performance of star trackers - a tutorial,” IEEE Trans. Aerosp. Electron. Syst. 38(2), 587–599 (2002).
[Crossref]

1965 (1)

G. Wahba, “A Least Squares Estimate of Satellite Attitude,” SIAM Rev. 7, 409 (1965).
[Crossref]

Bernelli-Zazzera, F.

L. Ma, F. Bernelli-Zazzera, S. Qin, and X. Wang, “Performance analysis of the attitude-correlated frames approach for star sensors,” in 2016 IEEE Metrology for Aerospace (MetroAeroSpace) (IEEE, 2016), pp. 81–86.
[Crossref]

Betto, M.

J. L. Jorgensen, T. Denver, M. Betto, and P. V. d. Braembussche, “The PROBA satellite star tracker performance,” Acta Astronautica 56, 153–159 (2005).
[Crossref]

Bezooijen, R. W. H. v.

R. W. H. v. Bezooijen, “SIRTF autonomous star tracker,” in Astronomical Telescopes and Instrumentation (SPIE, 2003), 14.

Braembussche, P. V. d.

J. L. Jorgensen, T. Denver, M. Betto, and P. V. d. Braembussche, “The PROBA satellite star tracker performance,” Acta Astronautica 56, 153–159 (2005).
[Crossref]

Chen, N.

F. Xing, N. Chen, Z. You, and T. Sun, “A Novel Approach Based on MEMS-Gyro’s Data Deep Coupling for Determining the Centroid of Star Spot,” Math. Probl. Eng. 2012, 403584(2012).

Chu, D.

T. Sun, F. Xing, X. Wang, Z. You, and D. Chu, “An accuracy measurement method for star trackers based on direct astronomic observation,” Sci. Rep. 6, 22593 (2016).
[Crossref] [PubMed]

Dai, D.

L. Ma, C. Hu, X. Wang, and D. Dai, “Advances and accuracy performance of the star trackers,” in ISPDI 2013 - Fifth International Symposium on Photoelectronic Detection and Imaging (SPIE, 2013), 9.

Denver, T.

J. L. Jorgensen, T. Denver, M. Betto, and P. V. d. Braembussche, “The PROBA satellite star tracker performance,” Acta Astronautica 56, 153–159 (2005).
[Crossref]

Fowell, R. A.

R. A. Fowell, S. I. Saeed, R. Li, and Y.-W. A. Wu, “Mitigation of angular acceleration effects on optical sensor data,” U.S. Patent 6, 863, 244 (2005).

R. A. Fowell, R. Li, and Y.-W. A. Wu, “Method for compensating star motion induced error in a stellar inertial attitude determination system,” U.S. Patent 7, 487, 016 (2009).

Fu, S.

L. Ma, D. Zhan, G. Jiang, S. Fu, H. Jia, X. Wang, Z. Huang, J. Zheng, F. Hu, W. Wu, and S. Qin, “Attitude-correlated frames approach for a star sensor to improve attitude accuracy under highly dynamic conditions,” Appl. Opt. 54, 7559–7566 (2015).
[Crossref] [PubMed]

S. Qin, D. Zhan, J. Zheng, W. Wu, H. Jia, S. Fu, and L. Ma, “Dynamic attitude measurement method of star sensor based on gyro’s precise angular correlation,” U.S. Patent 9,316,716 (2016).

Guo, L.

W. Zhang, W. Quan, and L. Guo, “Blurred Star Image Processing for Star Sensors under Dynamic Conditions,” Sensors 12, 6712 (2012).
[Crossref] [PubMed]

Hu, C.

L. Ma, C. Hu, X. Wang, and D. Dai, “Advances and accuracy performance of the star trackers,” in ISPDI 2013 - Fifth International Symposium on Photoelectronic Detection and Imaging (SPIE, 2013), 9.

Hu, F.

Hua, J.

J. Hua, T. Zhang, and H. Zhu, “Star image fusion and star recognition of multi-FOV star sensor,” in Proceedings of 2014 IEEE Chinese Guidance, Navigation and Control Conference (IEEE, 2014), pp. 2111–2125.

Huang, J.

J. Jiang, J. Huang, and G. Zhang, “An Accelerated Motion Blurred Star Restoration Based on Single Image,” IEEE Sensors Journal 17, 1306–1315 (2017).
[Crossref]

Huang, Z.

Jia, H.

L. Ma, D. Zhan, G. Jiang, S. Fu, H. Jia, X. Wang, Z. Huang, J. Zheng, F. Hu, W. Wu, and S. Qin, “Attitude-correlated frames approach for a star sensor to improve attitude accuracy under highly dynamic conditions,” Appl. Opt. 54, 7559–7566 (2015).
[Crossref] [PubMed]

S. Qin, D. Zhan, J. Zheng, W. Wu, H. Jia, S. Fu, and L. Ma, “Dynamic attitude measurement method of star sensor based on gyro’s precise angular correlation,” U.S. Patent 9,316,716 (2016).

Jiang, G.

Jiang, J.

J. Jiang, J. Huang, and G. Zhang, “An Accelerated Motion Blurred Star Restoration Based on Single Image,” IEEE Sensors Journal 17, 1306–1315 (2017).
[Crossref]

J. Yan, J. Jiang, and G. Zhang, “Dynamic imaging model and parameter optimization for a star tracker,” Opt. Express 24, 5961–5983 (2016).
[Crossref] [PubMed]

Jorgensen, J. L.

J. L. Jorgensen, T. Denver, M. Betto, and P. V. d. Braembussche, “The PROBA satellite star tracker performance,” Acta Astronautica 56, 153–159 (2005).
[Crossref]

Kan, X.

K. Wang, C. Zhang, Y. Li, and X. Kan, “A New Restoration Algorithm for the Smeared Image of a SINS-aided Star Sensor,” Journal of Navigation 67, 881–898 (2014).
[Crossref]

Li, A.

C. Liu, G. Liu, X. Wang, and A. Li, Principles and Systematic Applications of Missile-Borne Star Sensor (National Defense Industry, 2010).

Li, B.

Li, R.

R. A. Fowell, R. Li, and Y.-W. A. Wu, “Method for compensating star motion induced error in a stellar inertial attitude determination system,” U.S. Patent 7, 487, 016 (2009).

R. A. Fowell, S. I. Saeed, R. Li, and Y.-W. A. Wu, “Mitigation of angular acceleration effects on optical sensor data,” U.S. Patent 6, 863, 244 (2005).

Li, Y.

K. Wang, C. Zhang, Y. Li, and X. Kan, “A New Restoration Algorithm for the Smeared Image of a SINS-aided Star Sensor,” Journal of Navigation 67, 881–898 (2014).
[Crossref]

Liebe, C. C.

C. C. Liebe, “Accuracy performance of star trackers - a tutorial,” IEEE Trans. Aerosp. Electron. Syst. 38(2), 587–599 (2002).
[Crossref]

Liu, C.

C. Liu, G. Liu, X. Wang, and A. Li, Principles and Systematic Applications of Missile-Borne Star Sensor (National Defense Industry, 2010).

Liu, G.

C. Liu, G. Liu, X. Wang, and A. Li, Principles and Systematic Applications of Missile-Borne Star Sensor (National Defense Industry, 2010).

Ma, L.

L. Ma, D. Zhan, G. Jiang, S. Fu, H. Jia, X. Wang, Z. Huang, J. Zheng, F. Hu, W. Wu, and S. Qin, “Attitude-correlated frames approach for a star sensor to improve attitude accuracy under highly dynamic conditions,” Appl. Opt. 54, 7559–7566 (2015).
[Crossref] [PubMed]

L. Ma, F. Bernelli-Zazzera, S. Qin, and X. Wang, “Performance analysis of the attitude-correlated frames approach for star sensors,” in 2016 IEEE Metrology for Aerospace (MetroAeroSpace) (IEEE, 2016), pp. 81–86.
[Crossref]

L. Ma, C. Hu, X. Wang, and D. Dai, “Advances and accuracy performance of the star trackers,” in ISPDI 2013 - Fifth International Symposium on Photoelectronic Detection and Imaging (SPIE, 2013), 9.

S. Qin, D. Zhan, J. Zheng, W. Wu, H. Jia, S. Fu, and L. Ma, “Dynamic attitude measurement method of star sensor based on gyro’s precise angular correlation,” U.S. Patent 9,316,716 (2016).

Qin, S.

L. Ma, D. Zhan, G. Jiang, S. Fu, H. Jia, X. Wang, Z. Huang, J. Zheng, F. Hu, W. Wu, and S. Qin, “Attitude-correlated frames approach for a star sensor to improve attitude accuracy under highly dynamic conditions,” Appl. Opt. 54, 7559–7566 (2015).
[Crossref] [PubMed]

S. Qin, D. Zhan, J. Zheng, W. Wu, H. Jia, S. Fu, and L. Ma, “Dynamic attitude measurement method of star sensor based on gyro’s precise angular correlation,” U.S. Patent 9,316,716 (2016).

L. Ma, F. Bernelli-Zazzera, S. Qin, and X. Wang, “Performance analysis of the attitude-correlated frames approach for star sensors,” in 2016 IEEE Metrology for Aerospace (MetroAeroSpace) (IEEE, 2016), pp. 81–86.
[Crossref]

Quan, W.

W. Zhang, W. Quan, and L. Guo, “Blurred Star Image Processing for Star Sensors under Dynamic Conditions,” Sensors 12, 6712 (2012).
[Crossref] [PubMed]

W. Quan and W. Zhang, “Restoration of Motion-blurred Star Image Based on Wiener Filter,” in 2011 International Conference on Intelligent Computation Technology and Automation (IEEE, 2011), pp. 691–694.

Saeed, S. I.

R. A. Fowell, S. I. Saeed, R. Li, and Y.-W. A. Wu, “Mitigation of angular acceleration effects on optical sensor data,” U.S. Patent 6, 863, 244 (2005).

Sun, T.

T. Sun, F. Xing, X. Wang, Z. You, and D. Chu, “An accuracy measurement method for star trackers based on direct astronomic observation,” Sci. Rep. 6, 22593 (2016).
[Crossref] [PubMed]

T. Sun, F. Xing, Z. You, X. Wang, and B. Li, “Smearing model and restoration of star image under conditions of variable angular velocity and long exposure time,” Opt. Express 22, 6009–6024 (2014).
[Crossref] [PubMed]

F. Xing, N. Chen, Z. You, and T. Sun, “A Novel Approach Based on MEMS-Gyro’s Data Deep Coupling for Determining the Centroid of Star Spot,” Math. Probl. Eng. 2012, 403584(2012).

Titterton, D.

D. Titterton and J. L. Weston, Strapdown inertial navigation technology (IET, 2004).
[Crossref]

Wahba, G.

G. Wahba, “A Least Squares Estimate of Satellite Attitude,” SIAM Rev. 7, 409 (1965).
[Crossref]

Wang, K.

K. Wang, C. Zhang, Y. Li, and X. Kan, “A New Restoration Algorithm for the Smeared Image of a SINS-aided Star Sensor,” Journal of Navigation 67, 881–898 (2014).
[Crossref]

Wang, X.

T. Sun, F. Xing, X. Wang, Z. You, and D. Chu, “An accuracy measurement method for star trackers based on direct astronomic observation,” Sci. Rep. 6, 22593 (2016).
[Crossref] [PubMed]

L. Ma, D. Zhan, G. Jiang, S. Fu, H. Jia, X. Wang, Z. Huang, J. Zheng, F. Hu, W. Wu, and S. Qin, “Attitude-correlated frames approach for a star sensor to improve attitude accuracy under highly dynamic conditions,” Appl. Opt. 54, 7559–7566 (2015).
[Crossref] [PubMed]

T. Sun, F. Xing, Z. You, X. Wang, and B. Li, “Smearing model and restoration of star image under conditions of variable angular velocity and long exposure time,” Opt. Express 22, 6009–6024 (2014).
[Crossref] [PubMed]

L. Ma, F. Bernelli-Zazzera, S. Qin, and X. Wang, “Performance analysis of the attitude-correlated frames approach for star sensors,” in 2016 IEEE Metrology for Aerospace (MetroAeroSpace) (IEEE, 2016), pp. 81–86.
[Crossref]

L. Ma, C. Hu, X. Wang, and D. Dai, “Advances and accuracy performance of the star trackers,” in ISPDI 2013 - Fifth International Symposium on Photoelectronic Detection and Imaging (SPIE, 2013), 9.

C. Liu, G. Liu, X. Wang, and A. Li, Principles and Systematic Applications of Missile-Borne Star Sensor (National Defense Industry, 2010).

Weston, J. L.

D. Titterton and J. L. Weston, Strapdown inertial navigation technology (IET, 2004).
[Crossref]

Wu, W.

L. Ma, D. Zhan, G. Jiang, S. Fu, H. Jia, X. Wang, Z. Huang, J. Zheng, F. Hu, W. Wu, and S. Qin, “Attitude-correlated frames approach for a star sensor to improve attitude accuracy under highly dynamic conditions,” Appl. Opt. 54, 7559–7566 (2015).
[Crossref] [PubMed]

S. Qin, D. Zhan, J. Zheng, W. Wu, H. Jia, S. Fu, and L. Ma, “Dynamic attitude measurement method of star sensor based on gyro’s precise angular correlation,” U.S. Patent 9,316,716 (2016).

Wu, Y.-W. A.

R. A. Fowell, S. I. Saeed, R. Li, and Y.-W. A. Wu, “Mitigation of angular acceleration effects on optical sensor data,” U.S. Patent 6, 863, 244 (2005).

R. A. Fowell, R. Li, and Y.-W. A. Wu, “Method for compensating star motion induced error in a stellar inertial attitude determination system,” U.S. Patent 7, 487, 016 (2009).

Xing, F.

T. Sun, F. Xing, X. Wang, Z. You, and D. Chu, “An accuracy measurement method for star trackers based on direct astronomic observation,” Sci. Rep. 6, 22593 (2016).
[Crossref] [PubMed]

T. Sun, F. Xing, Z. You, X. Wang, and B. Li, “Smearing model and restoration of star image under conditions of variable angular velocity and long exposure time,” Opt. Express 22, 6009–6024 (2014).
[Crossref] [PubMed]

F. Xing, N. Chen, Z. You, and T. Sun, “A Novel Approach Based on MEMS-Gyro’s Data Deep Coupling for Determining the Centroid of Star Spot,” Math. Probl. Eng. 2012, 403584(2012).

Yan, J.

You, Z.

T. Sun, F. Xing, X. Wang, Z. You, and D. Chu, “An accuracy measurement method for star trackers based on direct astronomic observation,” Sci. Rep. 6, 22593 (2016).
[Crossref] [PubMed]

T. Sun, F. Xing, Z. You, X. Wang, and B. Li, “Smearing model and restoration of star image under conditions of variable angular velocity and long exposure time,” Opt. Express 22, 6009–6024 (2014).
[Crossref] [PubMed]

F. Xing, N. Chen, Z. You, and T. Sun, “A Novel Approach Based on MEMS-Gyro’s Data Deep Coupling for Determining the Centroid of Star Spot,” Math. Probl. Eng. 2012, 403584(2012).

Zhan, D.

L. Ma, D. Zhan, G. Jiang, S. Fu, H. Jia, X. Wang, Z. Huang, J. Zheng, F. Hu, W. Wu, and S. Qin, “Attitude-correlated frames approach for a star sensor to improve attitude accuracy under highly dynamic conditions,” Appl. Opt. 54, 7559–7566 (2015).
[Crossref] [PubMed]

S. Qin, D. Zhan, J. Zheng, W. Wu, H. Jia, S. Fu, and L. Ma, “Dynamic attitude measurement method of star sensor based on gyro’s precise angular correlation,” U.S. Patent 9,316,716 (2016).

Zhang, C.

K. Wang, C. Zhang, Y. Li, and X. Kan, “A New Restoration Algorithm for the Smeared Image of a SINS-aided Star Sensor,” Journal of Navigation 67, 881–898 (2014).
[Crossref]

Zhang, G.

J. Jiang, J. Huang, and G. Zhang, “An Accelerated Motion Blurred Star Restoration Based on Single Image,” IEEE Sensors Journal 17, 1306–1315 (2017).
[Crossref]

J. Yan, J. Jiang, and G. Zhang, “Dynamic imaging model and parameter optimization for a star tracker,” Opt. Express 24, 5961–5983 (2016).
[Crossref] [PubMed]

Zhang, T.

J. Hua, T. Zhang, and H. Zhu, “Star image fusion and star recognition of multi-FOV star sensor,” in Proceedings of 2014 IEEE Chinese Guidance, Navigation and Control Conference (IEEE, 2014), pp. 2111–2125.

Zhang, W.

W. Zhang, W. Quan, and L. Guo, “Blurred Star Image Processing for Star Sensors under Dynamic Conditions,” Sensors 12, 6712 (2012).
[Crossref] [PubMed]

W. Quan and W. Zhang, “Restoration of Motion-blurred Star Image Based on Wiener Filter,” in 2011 International Conference on Intelligent Computation Technology and Automation (IEEE, 2011), pp. 691–694.

Zheng, J.

L. Ma, D. Zhan, G. Jiang, S. Fu, H. Jia, X. Wang, Z. Huang, J. Zheng, F. Hu, W. Wu, and S. Qin, “Attitude-correlated frames approach for a star sensor to improve attitude accuracy under highly dynamic conditions,” Appl. Opt. 54, 7559–7566 (2015).
[Crossref] [PubMed]

S. Qin, D. Zhan, J. Zheng, W. Wu, H. Jia, S. Fu, and L. Ma, “Dynamic attitude measurement method of star sensor based on gyro’s precise angular correlation,” U.S. Patent 9,316,716 (2016).

Zhu, H.

J. Hua, T. Zhang, and H. Zhu, “Star image fusion and star recognition of multi-FOV star sensor,” in Proceedings of 2014 IEEE Chinese Guidance, Navigation and Control Conference (IEEE, 2014), pp. 2111–2125.

Acta Astronautica (1)

J. L. Jorgensen, T. Denver, M. Betto, and P. V. d. Braembussche, “The PROBA satellite star tracker performance,” Acta Astronautica 56, 153–159 (2005).
[Crossref]

Appl. Opt. (1)

IEEE Sensors Journal (1)

J. Jiang, J. Huang, and G. Zhang, “An Accelerated Motion Blurred Star Restoration Based on Single Image,” IEEE Sensors Journal 17, 1306–1315 (2017).
[Crossref]

IEEE Trans. Aerosp. Electron. Syst. (1)

C. C. Liebe, “Accuracy performance of star trackers - a tutorial,” IEEE Trans. Aerosp. Electron. Syst. 38(2), 587–599 (2002).
[Crossref]

Journal of Navigation (1)

K. Wang, C. Zhang, Y. Li, and X. Kan, “A New Restoration Algorithm for the Smeared Image of a SINS-aided Star Sensor,” Journal of Navigation 67, 881–898 (2014).
[Crossref]

Math. Probl. Eng. (1)

F. Xing, N. Chen, Z. You, and T. Sun, “A Novel Approach Based on MEMS-Gyro’s Data Deep Coupling for Determining the Centroid of Star Spot,” Math. Probl. Eng. 2012, 403584(2012).

Opt. Express (2)

Sci. Rep. (1)

T. Sun, F. Xing, X. Wang, Z. You, and D. Chu, “An accuracy measurement method for star trackers based on direct astronomic observation,” Sci. Rep. 6, 22593 (2016).
[Crossref] [PubMed]

Sensors (1)

W. Zhang, W. Quan, and L. Guo, “Blurred Star Image Processing for Star Sensors under Dynamic Conditions,” Sensors 12, 6712 (2012).
[Crossref] [PubMed]

SIAM Rev. (1)

G. Wahba, “A Least Squares Estimate of Satellite Attitude,” SIAM Rev. 7, 409 (1965).
[Crossref]

Other (10)

C. Liu, G. Liu, X. Wang, and A. Li, Principles and Systematic Applications of Missile-Borne Star Sensor (National Defense Industry, 2010).

R. W. H. v. Bezooijen, “SIRTF autonomous star tracker,” in Astronomical Telescopes and Instrumentation (SPIE, 2003), 14.

S. Qin, D. Zhan, J. Zheng, W. Wu, H. Jia, S. Fu, and L. Ma, “Dynamic attitude measurement method of star sensor based on gyro’s precise angular correlation,” U.S. Patent 9,316,716 (2016).

W. Quan and W. Zhang, “Restoration of Motion-blurred Star Image Based on Wiener Filter,” in 2011 International Conference on Intelligent Computation Technology and Automation (IEEE, 2011), pp. 691–694.

D. Titterton and J. L. Weston, Strapdown inertial navigation technology (IET, 2004).
[Crossref]

L. Ma, F. Bernelli-Zazzera, S. Qin, and X. Wang, “Performance analysis of the attitude-correlated frames approach for star sensors,” in 2016 IEEE Metrology for Aerospace (MetroAeroSpace) (IEEE, 2016), pp. 81–86.
[Crossref]

L. Ma, C. Hu, X. Wang, and D. Dai, “Advances and accuracy performance of the star trackers,” in ISPDI 2013 - Fifth International Symposium on Photoelectronic Detection and Imaging (SPIE, 2013), 9.

J. Hua, T. Zhang, and H. Zhu, “Star image fusion and star recognition of multi-FOV star sensor,” in Proceedings of 2014 IEEE Chinese Guidance, Navigation and Control Conference (IEEE, 2014), pp. 2111–2125.

R. A. Fowell, S. I. Saeed, R. Li, and Y.-W. A. Wu, “Mitigation of angular acceleration effects on optical sensor data,” U.S. Patent 6, 863, 244 (2005).

R. A. Fowell, R. Li, and Y.-W. A. Wu, “Method for compensating star motion induced error in a stellar inertial attitude determination system,” U.S. Patent 7, 487, 016 (2009).

Cited By

OSA participates in Crossref's Cited-By Linking service. Citing articles from OSA journals and other participating publishers are listed here.

Alert me when this article is cited.


Figures (14)

Fig. 1
Fig. 1 Definition of coordinate systems.
Fig. 2
Fig. 2 Model of angular velocity w, in 3 axes over 200s (left) and 10s (right) used within simulations.
Fig. 3
Fig. 3 The sensitivity of observation Δr to the CMIE ϕ. Subfigure axes have been scaled to highlight detail. (a) and (b) show the sensitivity of Δr(including Δrx and Δry) to ϕx. (c) and (d) show the sensitivity of Δr(including Δrx and Δry) to ϕy. (e) and (f) show the sensitivity of Δr(including Δrx and Δry) to ϕz.
Fig. 4
Fig. 4 Gradients of the fitted curves.
Fig. 5
Fig. 5 Flowchart of the proposed method.
Fig. 6
Fig. 6 Simulated star under shipboard dynamic conditions.
Fig. 7
Fig. 7 Simulation results of compensation of CMIE, and only 300 of all the emulated frames are plotted in order to display fine details. (a) The black curve is the attitude error of the centroiding method, and the red curve is the attitude error where the CMIE has been compensated for single FOV. (b) The black curve is the attitude error of the centroiding method, and the green curve is the attitude error where the CMIE has been compensated and the attitudes from different FOVs have been combined.
Fig. 8
Fig. 8 Simulation results of attitude error of the proposed method when N = 9. The green curve is the same as that in Fig. 7(b), and the blue curve is the result of the ACF approach when the number of frames N is 9.
Fig. 9
Fig. 9 Statistical results of the ACF approach. (a) The curves with different colors are the attitude errors with different methods. The dotted curves with the same color are the attitude errors under different number of frames N. The black curve represents the accuracy of the ACF approach on the raw data of centroiding method. The red curve represents the accuracy of the ACF approach, where the CMIE has been compensated for a single FOV. The green curve represents the accuracy of the ACF approach, where the CMIE has been compensated and the attitudes from different FOVs have been combined. (b) The green curve is the statistical results of the proposed method, which is the same as the curve with the same color in Part (a). The brown curve is the theoretical curve 1 / N. The yellow curve shows the relative deviation of the above two curves.
Fig. 10
Fig. 10 Experimental setup.
Fig. 11
Fig. 11 Three-axes angular velocity of the star tracker. Part (b) is partial enlarged detail of (a) in order to display fine details.
Fig. 12
Fig. 12 Experimental results of compensation of CMIE. (a) The black curve is the attitude error of the centroiding method, and the red curve is the attitude error where the CMIE has been compensated for single FOV. (b) The black curve is the attitude error of the centroiding method, and the green curve is the attitude error where the CMIE has been compensated and the attitudes from different FOVs have been combined.
Fig. 13
Fig. 13 Experimental results of the relative attitude error of the proposed method when N = 9. The green curve is the same as that in Fig. 12(b), and the blue curve is the result of the ACF approach when the number of frames N is 9.
Fig. 14
Fig. 14 Statistical results of the ACF approach. (a) The curves with different colors are the attitude errors with different methods. The dotted curves with the same color are the attitude errors under different number of frames N. The black curve represents the accuracy of the ACF approach on the centroiding data. The red curve represents the accuracy of the ACF approach, where the CMIE has been compensated for a single FOV. The green curve represents the accuracy of the ACF approach, where the CMIE has been compensated and the attitudes from different FOVs have been combined. (b) The green curve is the statistical results of the proposed method, which is the same as the curve with the same color in Part (a). The brown curve is the theoretical curve 1/N. The yellow curve shows the relative deviation of the above two curves.

Tables (3)

Tables Icon

Table 1 Simulation parameters

Tables Icon

Table 2 Statistical results of different compensation methods in the simulation (N=1, which means ACF is not applied)

Tables Icon

Table 3 Statistical results of different compensation methods in the experiment (N=1, which means ACF is not applied)

Equations (27)

Equations on this page are rendered with MathJax. Learn more.

{ P 1 = C 1 i S 1 + E 1 P 2 = C 2 i S 2 + E 2 P N = C N i S N + E N ,
E ss = FOV n pixel E centroid n ¯ star ,
{ [ P 1 , P 2 , , P N ] = C N i [ G 1 N S 1 , G 2 N S 2 , , S N ] + [ E 1 , E 2 , , E N ] G j N = l = j l = N 1 G l l + 1 , j = 1 , 2 , , N 1 .
C ^ ¯ N i = 1 N [ C ^ N i + C ^ N 1 i G N N 1 + + ( C ^ 1 i G 2 1 G 3 2 G N N 1 ) ] ,
S ^ j N = G j N S j + E j .
S ^ j N = G j N S j + G j N δ S j + E j .
{ [ P 1 , P 2 , , P N ] = C N i [ G 1 N S 1 , G 2 N S 2 , , S N ] + [ G 1 N δ S 1 , G 2 N δ S 2 , , δ S N ] + [ E 1 , E 2 , , E N ] G j N = l = j l = N 1 G l l + 1 , j = 1 , 2 , , N 1 .
{ X m = 1 T t 0 t 0 + T x ( t ) d t + Δ X m Y m = 1 T t 0 t 0 + T y ( t ) d t + Δ Y m ,
{ X p = 1 T t 0 t 0 + T x ^ ( t ) d t + Δ X p Y p = 1 T t 0 t 0 + T y ^ ( t ) d t + Δ Y p ,
{ r s ( t ) = [ x ( t ) , y ( t ) , f ] T r ^ s ( t ) = [ x ^ ( t ) , y ^ ( t ) , f ] T ,
{ r centroid s = [ X m , Y m , f ] T r ^ centroid s = [ X p , Y p , f ] T .
Δ r = r ^ centroid s r centroid s = [ Δ r x Δ r y 0 ] = [ X m X p Y m Y p 0 ] .
Δ r = 1 T t 0 t 0 + T [ r ^ s ( t ) r s ( t ) ] d t .
{ r ^ s ( t ) = C s ( t 0 ) s ( t 0 ) r ^ s ( t 0 ) r s ( t ) = C s ( t 0 ) s ( t 0 ) r s ( t 0 ) ,
Δ r = 1 T t 0 t 0 + T [ r ^ s ( t ) r s ( t ) ] d t = 1 T t 0 t 0 + T [ C s ( t 0 ) s ( t ) r ^ s ( t 0 ) C s ( t 0 ) s ( t ) r s ( t 0 ) ] d t = 1 T t 0 t 0 + T [ C s ( t 0 ) s ( t ) C s ( t 0 ) s ( t ) C s ( t 0 ) s ( t ) ] r ^ s ( t 0 ) d t .
Δ r 1 T t 0 t 0 + T C s ( t 0 ) s ( t ) [ I 3 × 3 C s ( t 0 ) s ( t ) ] r ^ s ( t 0 ) d t ,
C s ( t 0 ) s ( t ) = [ cos ϕ y cos ϕ z sin ϕ x sin ϕ y sin ϕ z cos ϕ y sin ϕ z + sin ϕ x sin ϕ y cos ϕ z cos ϕ x sin ϕ y cos ϕ x sin ϕ z cos ϕ x cos ϕ z sin ϕ x sin ϕ y cos ϕ z + sin ϕ x cos ϕ y sin ϕ z sin ϕ y sin ϕ z sin ϕ x cos ϕ y cos ϕ z cos ϕ x cos ϕ y ] .
C s ( t 0 ) s ( t 0 ) I 3 × 3 [ 0 ϕ z ϕ y ϕ z 0 ϕ x ϕ y ϕ x 0 ] = I 3 × 3 [ ϕ × ] .
Δ r = 1 T t 0 t 0 + T C s ( t 0 ) s ( t ) d t [ ϕ × ] r ^ s ( t 0 ) = ( 1 T t 0 t 0 + T C s ( t 0 ) s ( t ) d t ) [ r ^ s ( t 0 ) × ] ϕ = ( 1 T t 0 t 0 + T C g s C g ( t 0 ) g ( t ) C g s d t ) [ r ^ s ( t 0 ) × ] ϕ ,
[ r ^ s ( t 0 ) × ] = [ 0 f y ^ ( t 0 ) f 0 x ^ ( t 0 ) y ^ ( t 0 ) x ^ ( t 0 ) 0 ] .
Z = ( 1 T t 0 t 0 + T C g s C g ( t 0 ) g ( t ) C s g d t ) [ r ^ s ( t 0 ) × ] ,
Δ r = Z ϕ .
= ϕ ,
ϕ ^ = ( T ) 1 T .
C ˜ s i = ( I [ ϕ × ] ) C ^ s i ,
C = 1 T t 0 t 0 + T C g s C g ( t 0 ) g ( t ) C s g d t ,
Δ r = C [ r ^ s ( t 0 ) × ] ϕ = [ C 11 C 12 C 13 C 21 C 22 C 23 C 31 C 32 C 33 ] [ 0 f y ^ ( t 0 ) f 0 x ^ ( t 0 ) y ^ ( t 0 ) x ^ ( t 0 ) 0 ] ϕ = [ C 12 f + C 13 y ^ ( t 0 ) C 11 f C 13 x ^ ( t 0 ) C 11 y ^ ( t 0 ) + C 12 x ^ ( t 0 ) C 22 f + C 23 y ^ ( t 0 ) C 21 f C 23 x ^ ( t 0 ) C 21 y ^ ( t 0 ) + C 22 x ^ ( t 0 ) C 32 f + C 33 y ^ ( t 0 ) C 31 f C 33 x ^ ( t 0 ) C 32 y ^ ( t 0 ) + C 32 x ^ ( t 0 ) ] ϕ ,

Metrics